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With the rapid development of Wireless Local Area Network (WLAN) technique, the indoor WLAN localization has caught significant attention. In this paper, a novel indoor WLAN localization approach by using the high-dimensional manifold alignment with limited calibration load is proposed. Different from the conventional dimension-reduction based manifold alignment approach which preserves a limited part of the Received Signal Strength (RSS) data information, we first construct an innovative objective function from the augmented physical locations and the corresponding RSS data. Second, the closed-form solution to the objective function is obtained by applying the Lagrange multiplier approach. Finally, the target location is estimated at the closest point in the manifold. Furthermore, we present some preliminary analysis towards the generalization of the proposed objective function to the scenario with multiple …